CD token-tracker
Token 消耗追踪工具。当用户需要监控 API token 使用情况、生成每日/每周消耗报告、分析使用趋势时使用此 Skill。功能包括：自动记录每次对话的 token 消耗、生成数据表格报告、计算使用趋势和预测、支持定时推送日报。
Token 消耗追踪工具。当用户需要监控 API token 使用情况、生成每日/每周消耗报告、分析使用趋势时使用此 Skill。功能包括：自动记录每次对话的 token 消耗、生成数据表格报告、计算使用趋势和预测、支持定时推送日报。
As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
IntegrationSoftware developmentData and analyticstype and topics are labelled automatically from the skill text
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 7. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 41/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (token-tracker) differs from the folder (token-tracker-daily)
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 100Steps. 24 steps
- 100Execution cost. Instruction body is 1189 tokens
- 100Running it twice. No mutating operations
- low 10 top-level sections: this looks like several domains in one skill
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 117: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -212 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +4Structure: 22 headings
- +3Step-by-step instructions: 24 items
- +4Has examples (12 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.
External checks
ClawHub: suspicious
The skill appears intended for local token usage reporting, but review is warranted because it overstates automation, recommends persistent cron jobs, and its scripts can store data outside the documented skill folder.
LLM: suspicious (medium) · VirusTotal: · 12 Sept 2026